Reservoir Quality Prediction Research Articles

Controlling Factors of Meteoric Diagenesis in Karst Reservoirs: An Example from the Majiagou Formation, Ordos Basin, China

Karst reservoirs have always been a key field of oil and gas exploration. However, quantifying the process of meteoric transformation remains a persistent challenge that limits the accuracy of reservoir quality prediction. To explore the controlling factors of meteoric cementation on karst reservoirs, the Majiagou Formation of the Ordos Basin in China was selected as an example. The petrology; carbon, oxygen, and strontium isotopes; and in situ major, trace, and rare earth elements were used, types and origins of calcite cements were analyzed in detail. The results revealed five types of calcite cements (Cal-1~Cal-5), four types of cathodoluminescence (CL) intensities (dull, dull red, deep red, and bright red luminescence), and six types of rare earth element patterns (Pattern-1~Pattern-6). These five types of calcite cements developed in three periods. Cal-1 (transition CL) and Cal-2 (dull CL) were precipitated during the Early Pennsylvanian period, the meteoric freshwater was clean; Cal-3 (transition CL) and Cal-4 (bright red CL) were precipitated at the end of the Late Carboniferous period, the fluids had strong dissolution ability and were polluted by terrigenous debris; Cal-5 (transition CL) was deposited during the burial period, the fluid was pure pore water or groundwater. The control of the cement on the reservoir during the burial period was much weaker than that of meteoric cements. Therefore, explorations of karst reservoirs should be focused on weak cementation during the epigenetic period.

The characteristics and origin of chlorite coats in the Oligocene gas sandstone reservoirs of the Upper Huagang Formation, Xihu Depression, East China Sea Shelf Basin

Clay coats are widespread in the Oligocene braided river channel sandstones in the Xihu Depression on the East China Sea Shelf Basin. High clay coat coverage in braided channel sandstones is typically associated with good reservoir quality. The morphology, origin and distribution of clay coats and their effect on reservoir quality in different braided channel facies are investigated by core description, core analysis and a series of petrographic techniques. The present clay coats consist of two parts, the inner and outer coats. The inner coats are mainly composed of illite and chlorite components. The inner illite coats are transformed from smectitic clay precursors, while the inner chlorite coats may originate from thermally driven recrystallization of Fe-rich clay precursors. The outer clay coats, composed of well-crystallized chlorite, are possibly the result of neoformation directly from Fe- and Mg-rich pore water. The distribution of inner clay coats is controlled by sediment transport and deposition processes. The inner illite coats that are better developed in terms of content and thickness typically form in low energy braided channels due to relatively less transport abrasion of the smectitic clay precursors. The inner chlorite coats are observed exclusively in high energy mud clast-rich braided channels. The abundance of mud clasts and Fe-rich clay precursors are likely derived from the intense erosion of adjacent overbank mudstones, which are enriched in flocculated fluvial Fe oxides and hydroxides. The high coverage outer chlorite coats tend to occur in high energy braided channels with well-developed primary pores, since they provide sufficient growth space for chlorite. High energy braided channels with relatively low ductile component content generally maintain better porosity and permeability, which facilitates the development of the outer chlorite coats, thereby preserving more pore space by inhibiting quartz cementation and promoting subsequent dissolution of unstable silicate minerals, further improving reservoir quality. The results of this study provide new insights into the prediction of chlorite-coated reservoir quality of gas fields in Xihu Depression while also being relevant to braided river sandstones having comparable depositional settings worldwide.

Influence of the grain shape and packing texture on the primary porosity of sandstone: Insights from a numerical simulation

Sandstone is an important carrier of underground hydrocarbon and the geological sequestration of carbon dioxide. Primary porosity is an important parameter used to predict reservoir quality, and it is influenced by the grain shape, grain‐size distribution and grain packing texture. However, few studies have focused on deriving multivariate equations of the grain size, grain‐size distribution and grain packing texture to predict the primary porosity of sandstone. The natural sedimentary process of sandstones was designed and simulated using a discrete element method. The results confirmed that the primary porosity is influenced by roundness, flatness, elongation, grain‐size distribution and grain packing texture; of the attributes, the mean grain size contributes less to the primary porosity of sandstone. Based on 193 simulated sandstone samples with a one‐component grain packing texture, a mathematical model considering roundness, flatness, elongation, grain packing texture and grain‐size distribution was proposed. The maximum, mean absolute and root mean square errors were 0.71, 0.26 and 0.32, respectively. The correlation coefficient between the simulated results and mathematical predicted results was 0.94. Furthermore, the primary porosity was positively correlated with the kurtosis of the grain‐size distribution in sandstone with the same grain shape but different kurtosis. The primary porosity was found to be independent of the mean grain size and mainly affected by the grain packing texture. Moreover, the primary porosity prediction model for sandstones with different grain‐size distribution curves based on the grain packing texture, which was proposed by the author in a previous study, was verified, and the correlation coefficient between the simulated results and predicted results was >0.92. The new mathematical model proposed in this study is a useful supplement for key parameter acquisition in the previous primary porosity prediction model of sandstone with different grain‐size distribution curves and grain packing texture. A mathematical model considering roundness, flatness, elongation, grain packing texture and grain‐size distribution is of great significance for reservoir quality prediction and conducting a quantitative evaluation of the diagenesis.

Pore structure characteristics of different lithofacies of the Longmaxi shale, Western Hunan‐Hubei Region, China: Implications for reservoir quality prediction

Lithofacies and micropore characteristics of shale reservoir directly affect the exploration and development of natural gas. To determine the development potential of shales of the Longmaxi Formation in the Western Hunan‐Hubei Region, the lithofacies types and micropore structure characteristics of the Longmaxi Formation shales have been systematically studied in this paper, based on ordinary thin sections, argon ion polishing–scanning electron microscopy, physical property testing, x‐ray diffraction whole‐rock and clay mineral analysis, isothermal nitrogen, and carbon dioxide adsorptions. According to the principle of ‘laminar structure + total organic carbon (TOC) + mineral composition of felsic, clay, and carbonate minerals’, eight types of shale lithofacies were identified. The effective porosity of the Longmaxi shale ranges from 1.8% to 14.4%, with a peak range from 3% to 6%, while the permeability ranges from 0.001 to 1.27 mD, with an average of 0.106 mD. Combined with the isothermal adsorption experiments, the proportion of mesopores is the largest in the Longmaxi shale, followed by macropores and micropores. Moreover, the pore diameters of mesopores are concentrated between 3 and 10 nm, while those of micropores are concentrated between 0.4 and 0.9 nm. The pore volume of shale is most developed when the content of brittle felsic minerals is 50% ~ 75% and the content of clay minerals is 25% ~ 50%, and the TOC content is positively correlated with the pore volume and specific surface area. There are significant differences in the pore development characteristics of different lithofacies. The shale reservoir space analysis indicates that micropores are controlled by TOC content and clay minerals, while the macropores are controlled by depositional intergranular pores, TOC content, and felsic content, as well as diagenetic pyrite mould pores, microfractures pores, and intercrystalline pores. On the other hand, mesopores are related to a mix of depositional and diagenetic factors with dominant contribution of intergranular pores, intercrystalline pores, organic pores, and intergranular shrinkage fractures pores. It is found that the pore development of massive organic‐rich siliceous shale lithofacies has the best reservoir quality, including well‐connected intergranular pores, intercrystalline pores, organic pores, and shrinkage fractures. Therefore, the massive organic‐rich siliceous shale lithofacies is the dominant fine‐grained reservoir lithofacies in the studied area. Based on understating the pore characteristics of different lithofacies, this study can provide a scientific basis for the prediction of favourable sweet spots of shale gas reservoir in the Longmaxi Formation, western Hunan‐Hubei Region.

Prediction of lamina structure and reservoir quality in shale using well logs: The Cretaceous Qingshankou Formation, Gulong Sag, Songliao Basin, China

Lamina structure is determined by composition, thickness, continuity, and mineral assemblage. Reservoir quality in oil shale reservoirs is determined by lamina structure, which controls hydrocarbon accumulation and migration. The prediction and evaluation of multi-scale lamina structures using geophysical well logs is challenging. Recent studies demonstrate that the lamina structure classification may be based on core observation and core analysis. However, there are no corresponding high-resolution geophysical logging methods to identify and categorize lamina structure continuously in a single well. Here, an experimental approach, involving an integrated analysis of cores, thin sections, well logs such as slabs and button conductivity curves of image logs (up to 5 mm vertical resolution), is used to characterize lamina structure. T1-T2 (T1, longitudinal relaxation time, and T2, transverse relaxation time) maps of nuclear magnetic resonance (NMR) logs are applied to clarify the relationships between the lamina structure, reservoir quality, and oil-bearing properties. Results demonstrate how lamina structure in shale can be divided into three types: laminated rocks, layered rocks, and massive rocks, according to observation of core at the lamina scale. The thickness of individual lamina is less than 0.01 m in the laminated rocks, and the layered rocks have bundles of genetically related laminae thickness ranging between 0.01 m and 0.1 m. In massive rocks there is no visible layering. The well log response patterns of the three types of lamina structure are established so that the distribution of lamina structure can be predicted in a single well via well logs. Results show that the oil-bearing shale intervals are dominated by laminated rocks and layered rocks, accounting for 90% of the studied Qingshankou Formation. In addition, the layered rocks play an important role in improving reservoir quality and the laminated rocks present moderate reservoir quality. The massive rocks show poor reservoir quality. Moreover, an increased proportion of felsic mineral content favors increased oil potential in oil shale reservoirs. The method is generally applicable and is of value in developing predictive indicators of subsurface reservoir sweet spots in shale oil and gas exploration and development.

Reservoir quality evaluation and prediction in ultra-deep tight sandstones in the Kuqa depression, China

Core, thin sections, cathodoluminescence (CL), scanning electron microscopy (SEM), conventional well logs and image logs are used to unravel depositional microfacies, diagenetic facies and fractures in the deeply buried (6000–8100 m) Cretaceous Bashijiqike (K1bs) and Baxigai (K1bx) Formations in Kuqa depression of the Tarim Basin. Results show that depositional microfacies in core and well log data include distributary channel, river mouth bar and distributary bay deposits of fan-braided delta fronts as well as lacustrine deposits. We establish well log predictable models of depositional microfacies using conventional and image logs. The Cretaceous sandstones experienced low to medium mechanical compaction and low intensity dissolution. Dominant diagenetic minerals are carbonate cements, clay minerals and minor amounts of quartz cements. The pore spaces are primarily intergranular pores and rare dissolution pores. We identify three diagenetic facies according to compaction state and diagenetic minerals, including carbonate cemented facies, tightly compacted facies, and facies having limited compaction and lacking cement (slightly cemented and compacted facies). We use well log characteristics to interpret diagenetic facies in areas without core data. Fractures are also elements of reservoir quality, including vertical opening-mode fractures, high to medium dip angle fractures, low angle fractures that probably include small faults and horizontal fractures. Fractures include open, partially open, and closed (sealed) fractures. We used image logs to identify fracture attributes, and calculate fracture density, porosity, aperture, and length. Depositional microfacies and diagenetic facies determine the primary intergranular pores and diagenesis subsequently modified secondary pore spaces. Natural fractures acted as both reservoir porosity (probably less than 1%) and as hydrocarbon flow channels accounting for elevated permeability. We evaluate and predict reservoir quality by superposing depositional microfacies, diagenetic facies and fracture occurrence.

Multi-scale geophysical characterization of microporous carbonate reservoirs utilizing machine learning techniques: An analog case study from an upper Jubaila formation outcrop, Saudi Arabia

Microporosity hosts a significant portion of the total hydrocarbon volume in the Middle Eastern carbonate reservoirs. An improved understanding of microcrystals' morphology that hosts micropores, their impact on reservoir properties, and their spatial distributions will contribute to a more accurate reservoir quality prediction. This study proposes a methodology that utilizes machine learning approaches for microporosity characterization and integrates a multi-scale dataset ranging from micrometer-scale SEM images to meter-scale seismic attributes to build reservoir porosity models. We tested the methodology on an outcrop in Riyadh, Saudi Arabia, which exposes the upper part of the Jubaila Formation equivalent to the lower part of the Arab-D reservoir. We acquired a 35 m-long core and a 600 m-long 2D seismic line behind the outcrop. Laboratory-scale petrophysical measurements, including porosity, permeability, acoustic velocity, bulk and grain density, and x-ray diffraction, were performed over 106 horizontal core plugs drilled from the core. We quantitatively characterized the morphology and microtextures of micrite crystals using SEM images by performing Random Forest classifications trained on SEM image features. We performed unsupervised classification using Self-Organizing Map (SOM) to all lab-measured properties for data clustering. We investigated potential correlations between SOM clusters with micrite morphology, which resulted in a predictable relationship following the granularity and sphericity of microcrystals with porosity, permeability, and acoustic velocity. It was possible to represent multiple lithofacies with a single log-linear porosity-permeability relationship and a single value of equivalent differential effective medium (DEM) aspect ratio in velocity-porosity space. The inter-relationship between micrite morphology and microporosity in the well was then propagated to reservoir-grid scale using inverse differential effective medium (DEM) of acoustic impedance from inverted seismic data. The methodology developed in this study thus provides a practical way to integrate key sub-grid scale micro-and macro-heterogeneities into reservoir scale property models.

Integrated Diagenetic-Depositional Facies (IDDF) characterization and 3D geomodeling in carbonate reservoirs

Carbonate reservoirs are very prone to diagenetic modification of pre-existing fabrics. The process around the modification of pre-existing depositional fabrics is often interrelated with diagenetic phases that impact reservoir quality and distribution. Characterization and 3D modeling of these features have always been a challenge in the upstream industry. This paper outlines a novel workflow for characterizing and modeling the Integrated Diagenetic-Depositional Facies (IDDF) in carbonate reservoirs, from 1D IDDF classification and Neural Network (NN) estimation, to 2D IDDF trend and seismic-based probability region modeling, culminating with the 3D geo-cellular modeling processes. The workflow integrates several geoscience data sets including; linking of petrographic thin sections analyses with other scales of data from core descriptions, well-logs signatures, Routine Core Analyses (RCA), Production Logging Tool (PLT) inflow analyses, diagenetic proxies and depositional concepts. The IDDF workflow ties these features with 3D seismic attribute region extraction to benefit 3D geo-cellular property modeling. This workflow greatly improves reservoir quality prediction, 3D reservoir modeling and volume estimation.

Impact of depositional and diagenetic controls on reservoir quality of syn-rift sedimentary systems: An example from Oligocene-Miocene Al Wajh Formation, northwest Saudi Arabia

Tertiary, syn-rift clastic reservoirs offer a unique opportunity to investigate the pivotal role of depositional and early diagenetic controls on reservoir quality. The Al Wajh Formation is a vital exploration target for petroleum in the Red Sea, and is characterized by early, near-surface diagenetic signatures. An integrated petrographic-mineralogical study is conducted to assess the role of depositional factors (e.g., sand grain size and clay matrix) and early diagenetic overprints on reservoir quality. The Al Wajh sandstones are primarily subarkose and lithic arkose, deposited in alluvial fan, braided fluvial, and nearshore environments. Braided fluvial sandstones of the formation have the best quality reservoirs (average porosity: 23.2 %; average permeability: 3025 mD) because of medium to coarse grain size and small proportion of clay matrix, whereas the nearshore sandstones form reservoirs of far lower quality (average porosity: 12.6 %; average permeability: 486 mD) owing to predominantly finer grain size and higher proportion of clay matrix. Clay volume between 10 and 20 % generally reduces the reservoir properties to <10 % porosity and 100 mD permeability. Compaction and grain dissolution are the major near-surface, early diagenetic processes that have strongly affected the sandstones reservoir quality. High mechanical compaction has been recorded in sandstones characterized by abundant matrix content and ductile rock fragments. Dissolution of labile grains (e.g., feldspars) has created secondary, intragranular porosity of up to 13.5 % (average 4.7 %). Kaolinite is the primary authigenic pore-filling clay in the continental units of the formation, whereas detrital and authigenic smectites are the key pore-filling clays in the nearshore units of the formation. Grain-coating smectite (up to 18.7 %; average: 7.1 %) was mainly emplaced through mechanical infiltration and has the potential for inhibiting quartz cementation should deep burial occur. The findings of the study can be utilized for modelling reservoir quality in the subsurface analogue of the Al Wajh Formation in the Red Sea or elsewhere, thereby improving reservoir quality prediction.

Controls on anomalously high porosity/permeability of Middle Jurassic deeply buried tight sandstones in the Taibei Sag, Turpan-Hami Basin, northwestern China: Implications for reservoir quality prediction

The lower member of the Middle Jurassic Xishanyao Formation (J2x1+2) sandstones are significant exploratory targets for hydrocarbon resources in the Taibei Sag of the Turpan-Hami Basin, northwestern China. Formation of anomalously high porosity/permeability in deeply buried J2x1+2 sandstones and reservoir quality prediction were investigated using a variety of petrographic analyses. These results show that the J2x1+2 sandstones are mostly feldspathic litharenites and litharenites, which are characterized by moderate-to good sorting, silty to medium granularity, and point- to long grain contacts. The J2x1+2 sandstone has low porosity (avg 6.0%) and permeability (avg 1.12 mD), but shows anomalously high porosity/permeability at depth interval of 3850–4050 m. There is a noticeable variation in pore types and sizes from intergranular-intragranular dissolution pores with a size mode of 2.0 μm in anomalously high porosity (AHP) sandstones, to major intragranular dissolution pores with a size mode of 0.5 μm in normally high porosity (NHP) sandstones, to most micropores with a size mode of 0.25 μm occurred in the normally low porosity (NLP) sandstones. The compaction is the main cause of porosity destruction, resulting in an average porosity loss of 89.6%. However, the authigenic minerals have relatively little influence on reservoir quality. The combination of nappe tectonics and well-sorted particles alleviated the compaction and thus preserved more intergranular pores in the AHP sandstones. Dissolution further increases the porosity and eventually forms the AHP sandstones. The strong carbonate-cemented facies (SCC), tightly compacted facies (TC), moderately compacted with moderate dissolution facies (MCMD), and weakly compacted with strong dissolution facies (WCSD) are determined in the J2x1+2 sandstones. The sandstones with SCC and TC are recognized as the NLP reservoirs. The MCMD and WCSD correspond to the NHP and AHP reservoirs, respectively. The reservoir quality predicted using the constructed diagenetic facies charts is in good agreement with the photomicrograph observations and physical property tests. Additionally, the AHP reservoirs are still developed in the deeply buried sandstones with depths larger than 4000 m.

Elaborated Porosity and High-Quality Reservoirs in Deeply Buried Coarse-Grained Sediment: Insight of the Sublacustrine Sandy Conglomerates in the Eocene Shehejie Formation (Es4), Dongying Subbasin, Bohai Bay Basin, China

Reservoir porosity evaluation is crucial for successful prediction of reservoir quality in deeply buried heterogeneous strata. Recent studies have demonstrated that high-quality reservoirs occur in deeply buried strata. However, little is known about the details of pores related to the good reservoirs. The northern Dongying steep slope sandy conglomerate was investigated to understand the porosity related to high-quality reservoir formation in sandy conglomerate using seismic data, well-logs, SEM-EDS, cathodoluminescence, and optical microscopy. The result reveals three genetic pores: primary, secondary, and mixed pores. The dissolution porosity consists of intergranular pores, intragranular pores, intercrystalline pores, and moldic pores. The intergranular dissolution and enlarged pores are the main contributors to good reservoir quality among the different pores. The index of compaction indicates that compaction is the crucial factor diminishing the reservoir quality in the progradation sequences, while cementation stands as the critical factor for porosity reduction in the retrogradation sequences. Comparing the reservoir properties reveals that the dissolution porosity is more significant in the Es4s than the Es4x, which renders the Es4s reservoir relatively good compared to the Es4x. This study demonstrated that for oil exploration in the fourth member of the Shahejie Formation, the Es4s should be prioritized.

A Comparative Study on the Microstructure and Petrophysical Properties of Undeformed and Naturally Deformed Shales

Structural deformation is one of the main impacts responsible for understanding the hydrocarbon accumulation mechanism. Predicting its function in gas storage and migration in a microscopic scale is thus a significant issue in predicting reservoir quality. The purpose of this article is to make a comparative study on the microstructure and petrophysical properties of undeformed and naturally deformed shales developed in the Southeast Sichuan Basin. The results show that (1) organic pores, ranging from 10 to 200 nm, are more developed in undeformed shale, whereas carbonate solvopores, clay-hosted pores, and microfractures are dominant in deformed shale. (2) Undeformed shales have Dubinin–Radushkevich (DR) CO2 adsorbed contents ranging between 0.009 and 0.018 g, DR CO2 micropore surface areas of 3.90–15.59 m2/g, and Dubinin–Astakhov (DA) CO2 micropore volumes of 0.002 and 0.035 cc/g. Naturally deformed shales have larger DR CO2 adsorbed contents, DR CO2 micropore surface areas, and DA CO2 micropore volumes, typically in the ranges of 0.019–0.031 g, 13.15–20.97 m2/g, and 0.006–0.012 cc/g, respectively. (3) Undeformed shales have N2 adsorbed contents ranging between 1.94 and 6.03 cc/g, Brunauer–Emmett–Teller (BET) N2 mesopore and macropore surface areas of 0.55–7.35 m2/g, and Barrett–Joyner–Halenda (BJH) N2 mesopore and macropore volumes of 0.002 and 0.006 cc/g. Naturally deformed shales have larger N2 adsorbed contents, BET N2 mesopore and macropore surface areas, and BJH N2 mesopore and macropore volumes, typically in the ranges of 5.72–14.45 cc/g, 7.47–17.64 m2/g, and 0.005–0.015 cc/g, respectively. (4) All samples have a unimodal micropore size distribution with a distinct peak associated with a 1.5 nm micropore fraction and have a multimodal mesopore and macropore size distribution. Naturally deformed shales show more homogeneous pore size distribution curves with morphological consistency than undeformed shales, indicating that structural deformation can significantly influence pore structural heterogeneity. (5) Deformed shales exhibit higher porosity and permeability compared to the undeformed samples due to the open pore-fracture network associated with the inorganic pores and microfractures. Average porosity and permeability in deformed shales can be 1.8 and 15 times higher than those in the undeformed shales. We conclude that the microstructural heterogeneity from strong to weak and the changes of a relatively single organic pore-dominated pore system to complex pores and microfractures dominated the pore-fracture system within shales due to structural deformation being the key cause of the quantitatively and qualitatively studied microstructure and petrophysical property differences.

Prograding early to middle Jurassic margin, Neuquén Basin: Topset process stratigraphy and morphodynamic sediment partitioning

AbstractNew Cuyo Group outcrop data complement recently published seismic and well data that detail the progradational character of the Lower‐Middle Jurassic Neuquén Margin (Argentina). The deepwater margin, with shelf topset (Lajas Formation), slope break and deepwater slope to basin‐floor deposits (Los Molles Formation), prograded northward and westward as large‐scale clinoforms (250–500 m high) for 120 km, during 13 My, supplied by sediment mainly from the North Patagonian Massif. The studied Lajas Formation topsets are themselves progradational, with a 500 m‐thick vertical succession of subaqueous delta, shoreface with associated tidal flat, mouth bar, fluvio‐tidal channel and alluvial plain deposits. This pattern is confirmed by facies analysis in five areas of outcrops and well data but is interrupted by frequent marine transgressions that add a short‐term cyclicity to the succession. A new paleogeographic map suggests previous disagreements on process stratigraphy are due to shoreline/paralic strike variability and to increased basinal process impact as the topset/shelf widened. A marked feature of each Lajas topset sequence is a differential partitioning of sand and mud, though not with a simple proximal to distal grain‐size reduction. The sand‐prone outer shelf passes landward to a channelized muddy shoreline environment, and then to a mixed sandy and muddy channelized coastal and alluvial plain. This type of partitioning, important for the characterization and prediction of reservoir quality, can also be recognized on seismic and well log data.

Reservoir Quality Prediction of Gas-Bearing Carbonate Sediments in the Qadirpur Field: Insights from Advanced Machine Learning Approaches of SOM and Cluster Analysis

The detailed reservoir characterization was examined for the Central Indus Basin (CIB), Pakistan, across Qadirpur Field Eocene rock units. Various petrophysical parameters were analyzed with the integration of various cross-plots, complex water saturation, shale volume, effective porosity, total porosity, hydrocarbon saturation, neutron porosity and sonic concepts, gas effects, and lithology. In total, 8–14% of high effective porosity and 45–62% of hydrocarbon saturation are superbly found in the reservoirs of the Eocene. The Sui Upper Limestone is one of the poorest reservoirs among all these reservoirs. However, this reservoir has few intervals of rich hydrocarbons with highly effective porosity values. The shale volume ranges from 30 to 43%. The reservoir is filled with effective and total porosities along with secondary porosities. Fracture–vuggy, chalky, and intracrystalline reservoirs are the main contributors of porosity. The reservoirs produce hydrocarbon without water and gas-emitting carbonates with an irreducible water saturation rate of 38–55%. In order to evaluate lithotypes, including axial changes in reservoir characterization, self-organizing maps, isoparametersetric maps of the petrophysical parameters, and litho-saturation cross-plots were constructed. Estimating the petrophysical parameters of gas wells and understanding reservoir prospects were both feasible with the methods employed in this study, and could be applied in the Central Indus Basin and anywhere else with comparable basins.

Impact of grain-coating illite in preventing quartz cementation: Example from permo-carboniferous sandstone, Central Saudi Arabia

The origin and role of clay coatings (e.g., chlorite) in inhibiting quartz cementation in sandstones have been an area of research during the last three decades. However, the role of grain-coating illite in porosity preservation has received little attention. An integrated petrographic-mineralogical study is conducted to investigate the mode of occurrence of illite coatings, their coverage, thickness, and role in inhibiting the development of quartz overgrowth in a Permo-Carboniferous sandstone reservoir in Central Saudi Arabia. Results of the study reveal that illite coatings occur in two forms: tangential and radial to grain surfaces, both of which are effective in arresting quartz cementation. Illite-coating coverage exhibits and inverse relationship with quartz cement volume, and the coating coverage has been found to be grain-size dependent. Coarser-grained sandstones have higher coating coverage due to smaller surface area and smaller amount of illite required to form complete coatings. The study has found that thick illite coating (up to 27 μm) and high illite-coating coverage (≥80%) effectively arrest quartz cementation. Total pore-filling cements threshold of >20% has a negative impact on porosity. The findings of this study can be applied to other reservoirs of similar depositional environments to improve their reservoir quality prediction.

Prediction of multiscale laminae structure and reservoir quality in fine-grained sedimentary rocks: The Permian Lucaogou Formation in Jimusar Sag, Junggar Basin

Fine-grained sedimentary rocks have become a research focus as important reservoirs and source rocks for tight and shale oil and gas. Laminae development determines the accumulation and production of tight and shale oil and gas in fine-grained rocks. However, due to the resolution limit of conventional logs, it is challenging to recognize the features of centimeter-scale laminae. To close this gap, complementary studies, including core observation, thin section, X-ray diffraction (XRD), conventional log analysis, and slabs of image logs, were conducted to unravel the centimeter-scale laminae. The laminae recognition models were built using well logs. The fine-grained rocks can be divided into laminated rocks (lamina thickness of <0.01 m), layered rocks (0.01–0.1 m), and massive rocks (no layer or layer spacing of >0.1 m) according to the laminae scale from core observations. According to the mineral superposition assemblages from thin-section observations, the laminated rocks can be further divided into binary, ternary, and multiple structures. The typical mineral components, slabs, and T 2 spectrum distributions of various lamina types are unraveled. The core can identify the centimeter–millimeter-scale laminae, and the thin section can identify the millimeter–micrometer-scale laminae. Furthermore, they can detect mineral types and their superposition sequence. Conventional logs can identify the meter-scale layers, whereas image logs and related slabs can identify the laminae variations at millimeter–centimeter scales. Therefore, the slab of image logs combined with thin sections can identify laminae assemblage characteristics, including the thickness and vertical assemblage. The identification and classification of lamina structure of various scales on a single well can be predicted using conventional logs, image logs, and slabs combined with thin sections. The layered rocks have better reservoir quality and oil-bearing potential than the massive and laminated rocks. The laminated rocks’ binary lamina is better than the ternary and multiple layers due to the high content of felsic minerals. The abovementioned results build the prediction model for multiscale laminae structure using well logs, helping sweet spots prediction in the Permian Lucaogou Formation in the Jimusar Sag and fine-grained sedimentary rocks worldwide.

New direction for regional reservoir quality prediction using machine learning - Example from the Stø Formation, SW Barents Sea, Norway

Recently, the petroleum industry has focused on deeply buried reservoir discoveries and exploring potential CO2 storage sites close to existing infrastructure to increase the life span of already operating installations to save time and cost. It is therefore essential for the petroleum industry to find an innovative approach that exploits the existing core- and well log data to be successful in their endeavor of effectively characterizing and predicting reservoir quality. Continuous data sources (e.g. wireline logs) have a huge potential compared with expensive, time inefficient and sporadic data from cores in determining reservoir quality for use in a regional context. However, whereas core analysis offers in-depth knowledge about rock properties and diagenetic processes, continuous data sources can be difficult to interpret without a formation-specific framework. Here, we demonstrated how the pre-existing core data could be effectively used by integrating petrographic- and facies data with a pure predictive machine learning (ML) based porosity predictor. The inclusion of detailed core analysis is important for determining which reservoir parameter(s) that should be modeled and for the interpretation of model outputs. By applying this methodology, a framework for deducing lithological and diagenetic attributes can be established to aid reservoir quality delineation from wireline logs that can be used in frontier areas. With the ML porosity model, a Random Forest Regressor, the square of the correlation was 0.84 between predicted- and helium porosity test data over a large dataset consisting of 38 wells within the Stø Formation across the SW Barents Sea. By integrating the continuous ML porosity logs and core data, it was possible to differentiate three distinct bed types on wireline log responses within the Stø Formation. Particularly, the relationship between Gamma ray (GR) and porosity was effective in separating high porosity clean sand-, low porosity cemented clean sand and more clay and silt rich intervals. Additionally, in the P-wave velocity (VP) - density domain, separation of high porosity clean sand- and heavily cemented low porosity clean sand intervals were possible. The results also show that the ML derived porosity curves coincide with previously published and independent facies data from a selection of the wells included in the study. This demonstrates the applicability of the model in the region, because the Stø Formation has been described to exhibit similar lithological- and mineralogical properties over large parts of the Western Barents Sea area. Even though, continuous porosity data could be estimated from other sources like VP, neutron or density logs, this would generally require matrix and fluid information. This study demonstrated the effectiveness of the ML model in generating continuous porosity logs that are useful for characterizing and predicting reservoir properties in new wells. This methodology offers a workflow for exploiting already acquired core and well log data for frontier exploration that can be adapted to other formations and exploration scenarios worldwide.

Sand-ratio distribution in an unconventional tight sandstone reservoir of Hangjinqi area, Ordos Basin: Acoustic impedance inversion-based reservoir quality prediction

Future gas field development and prospect assessment depend on accurate reservoir parameter characterization. The understanding of the tight sand distribution of the Shanxi and Taiyuan Formations within the Hangjinqi area is ambiguous due to the presence of coal and mudstone lithofacies, high heterogeneity, and poor resolution of the seismic data. Thus, it is difficult to determine the reservoir’s thickness. To cope with this challenge, we have employed the advanced method of constrained sparse spike inversion (CSSI) utilizing 3D seismic and nine wells for the distinction of tight sandstone facies from the coal and mudstone facies. Results of petrophysical analysis of studied well J54 show that the coal and mudstone facies are dominant towards the T9c horizon, whereas tight sandstone facies are present towards the T9d horizon. The obtained findings show that the CSSI accurately identified the spatial distribution of sand-ratio in the zone of interest (ZOI) that lies between the T9c and T9d horizons. The acoustic impedance (AI) of coal shows the lowest AI values, whereas the tight sandstone shows the highest AI values. The tight sandstone facies shows moderate values of AI in the range of 8.5 × 106 kg/m2s to 1.20 × 107 kg/m2s. The impedance map of T9c suggested the presence of coal and mud facies, whereas the T9d impedance map suggest the presence of maximum tight sandstone facies. The sand-ratio map of T9d showed maximum reservoir thickness that ranges from 0.65-0-95, whereas the sand-ratio value mostly ranges from 0 to 0.5 on the T9c map. The maximum sand-ratio values on T9d show that the lower Shanxi Formation has good reservoir characteristics. Whereas, due to the presence of coal and mudstone in the Taiyuan Formation, the T9c map shows low values of sand-ratio. The maximum sand-ratio regions within the targeted T9c-T9d layers should be exploited for future gas explorations.

An integrated sedimentological, rock typing, image logs, and artificial neural networks analysis for reservoir quality assessment of the heterogeneous fluvial-deltaic Messinian Abu Madi reservoirs, Salma field, onshore East Nile Delta, Egypt

This study introduces an integrated evaluation of geological and geophysical data, including sedimentology, diagenetic alteration, image log analysis, core measurements, formation evaluation, and a neural analysis technique (K-mode algorithm) to characterize the upper Messinian heterogeneous reservoirs of the Salma Field, Nile Delta, Egypt. It links observed reservoir permeability and flow zone indicators (FZI) to predict reservoir quality and distribution within un-cored parts of the field. Core and image log analysis show that the Abu Madi sandstone reservoir is composed of seven clastic litho-facies deposited within fluvial to deltaic environments. The reservoir is controlled by four hydraulic flow units (HFU's) and five flow units (FU). Fluvial channel facies, tidally influenced fluvial channel facies, and uppermost parts of bayhead delta facies are dominated by clean sandstone with a low clay content (avg. 20%). These facies are characterized by the high pore-throat sizes (R35 and FZI values), indicating a pore system dominated by mega-to macro-pores. The estuarine facies is composed of mudstone, siltstone, and argillaceous sandstone, with 25% average clay content and moderate R35 and FZI values, indicating a pore system dominated by macro-to meso-pores. The heterolithic estuarine and bayhead delta facies contain abundant argillaceous-rich sandstones, with 29% average clay content and low R35 and FZI values, indicating a pore system dominated by micro-pores. A neural log technique was applied to predict FZIs and permeability in un-cored intervals. Paleocurrent analysis was conducted using image log data to guide sweet spot and reservoir quality tracking across the field. Reservoir quality is controlled by both diagenetic and depositional processes, chiefly an abundance of detrital clays, grain size, and sorting. In the Salama Field reservoirs, mineral dissolution, cement dissolution, and micro-fractures enhance the pore system, while pore-filling and grain-coating detrital clays reduce reservoir quality. These results are important as they improve the wider understanding of the Messinian Abu Madi reservoir in the wider Mediterranean region.

A New Image Processing Workflow for the Detection of Quartz Types in Shales: Implications for Shale Gas Reservoir Quality Prediction

A shale lithofacies scheme is commonly used to characterize source rock reservoirs of the Lower Cambrian Niutitang Formation. However, this classification ignores that individual components such as quartz may have different origins, potentially affecting reservoir quality. The main objective of this article is, therefore, to present a refined scheme for lithofacies and an image processing workflow for the detection of quartz types in the Niutitang Formation shales from the Jiumen outcrop in the Guizhou Province (Upper Yangtze Basin, SW China). In order to do so, a combination of bulk density, optical and scanning electron microscopy and image analysis was used. The shale lithology was macroscopically classified into seven major categories and nineteen subcategories. Subsequently, the shales were investigated at the microscopic level, mainly focusing on quartz types and microstructural variations. Afterwards, the workflow to calculate the weight per unit volume (1 cm3) of the quartz types was presented, i.e., firstly, by calculating the weight of mineral matter by subtraction of the measured weight of organic matter from the bulk shale; secondly, by calculating the weight of total quartz in bulk shale from the weight of mineral matter and its proportion calculated from X-ray diffraction data; thirdly, by calculating the weight of detrital quartz and non-detrital quartz with energy dispersive X-ray mapping, image processing and quartz density; finally, by calculating the weight of clay-sized quartz by subtracting of the weight of detrital and non-detrital quartz from the weight of the total quartz. The bulk quartz content was found to be dominated by clay-sized quartz, which may mainly control the mesopore volume available for gas storage and, hence, the shale gas reservoir development.